Video quality using outpatient smartphone videos in epilepsy: Results from the OSmartViE study.

BACKGROUND AND PURPOSE: The aim of this study was to evaluate the quality of smartphone videos (SVs) of neurologic events in adult epilepsy outpatients. The use of home video recording in patients with neurological disease states is increasing. Experts interpretation of outpatient smartphone videos of seizures and neurological events has demonstrated similar diagnostic accuracy to inpatient video-electroencephalography (EEG) monitoring. METHODS: A prospective, multicenter cohort study was conducted to evaluate SV quality in patients with paroxysmal neurologic events from August 15, 2015 through August 31, 2018. Epileptic seizures (ESs), psychogenic nonepileptic attacks (PNEAs), and physiologic nonepileptic events (PhysNEEs) were confirmed by video-EEG monitoring. Experts and senior neurology residents blindly viewed cloud-based SVs without clinical information. Quality ratings with regard to technical and operator-driven metrics were provided in responses to a survey. RESULTS: Forty-four patients (31 women, age 45.1 years [r = 20-82]) were included and 530 SVs were viewed by a mean of seven experts and six residents; one video per patient was reviewed for a mean of 133.8 s (r = 9-543). In all, 30 patients had PNEAs, 11 had ESs, and three had PhysNEEs. Quality was suitable in 70.8% of SVs (375/530 total views), with 36/44 (81.8%) patient SVs rated as adequate by the majority of reviewers. Accuracy improved with the presence of convulsive features from 72.4% to 98.2% in ESs and from 71.1% to 95.7% in PNEAs. An accurate diagnosis was given by all reviewers (100%) in 11/44 SVs (all PNEAs). Audio was rated as good by 86.2% of reviewers for these SVs compared with 75.4% for the remaining SVs (p = 0.01). Lighting was better in SVs associated with high accuracy (p = 0.06), but clarity was not (p = 0.59). Poor video quality yielded unknown diagnoses in 24.2% of the SVs reviewed. Features hindering diagnosis were limited interactivity, restricted field of view and short video duration. CONCLUSIONS: Smartphone video quality is adequate for clinical interpretation in the majority of patients with paroxysmal neurologic events. Quality can be optimized by encouraging interactivity with the patient, adequate duration of the SV, and enlarged field of view during videography. Quality limitations were primarily operational though accuracy remained for SV review of ESs and PNEAs.

Focal nonmotor versus motor seizures: The impact on diagnostic delay in focal epilepsy.

OBJECTIVE: To test the hypothesis that people with focal epilepsy experience diagnostic delays that may be associated with preventable morbidity, particularly when seizures have only nonmotor symptoms, we compared time to diagnosis, injuries, and motor vehicle accidents (MVAs) in people with focal nonmotor versus focal seizures with motor involvement at epilepsy onset. METHODS: This retrospective study analyzed the enrollment data from the Human Epilepsy Project, which enrolled participants between 2012 and 2017 across 34 sites in the USA, Canada, Europe, and Australia, within 4 months of treatment for focal epilepsy. A total of 447 participants were grouped by initial seizure semiology (focal nonmotor or focal with motor involvement) to compare time to diagnosis and prediagnostic injuries including MVAs. RESULTS: Demographic characteristics were similar between groups. There were 246 participants (55%) with nonmotor seizures and 201 participants (45%) with motor seizures at epilepsy onset. Median time to diagnosis from first seizure was 10 times longer in patients with nonmotor seizures compared to motor seizures at onset (P < .001). The number and severity of injuries were similar between groups. However, 82.6% of MVAs occurred in patients with undiagnosed nonmotor seizures. SIGNIFICANCE: This study identifies reasons for delayed diagnosis and consequences of delay in patients with new onset focal epilepsy, highlighting a treatment gap that is particularly significant in patients who experience nonmotor seizures at epilepsy onset.

Digital and technological opportunities in epilepsy: Toward a digital ecosystem for enhanced epilepsy management.

This commentary details the implications of a growing body of literature supporting several categories of supportive digital tools for the self-management of epilepsy. Although many prior review articles have focused on specific forms of digital epilepsy solutions, we propose the concept of an integrated self-management digital ecosystem. This would include categories of tools including self-management education programs, electronic diaries for self-monitoring, and automated wearables for seizure detection. Within these categories, individual interventions have been studied and made available to patients for years, but the evolution of a digital ecosystem promises the potential to integrate these tools in a manner that can meaningfully benefit patients' health. This commentary presents a discussion of the possible concerns that are preventing more widespread adoption of these digital health resources. Barriers are identified at multiple positions of the healthcare system, including the individual, the organizational, the community, and the policy levels.

Common data elements for epilepsy mobile health systems.

OBJECTIVE: Common data elements (CDEs) are currently unavailable for mobile health (mHealth) in epilepsy devices and related applications. As a result, despite expansive growth of new digital services for people with epilepsy, information collected is often not interoperable or directly comparable. We aim to correct this problem through development of industry-wide standards for mHealth epilepsy data. METHODS: Using a group of stakeholders from industry, academia, and patient advocacy organizations, we offer a consensus statement for the elements that may facilitate communication among different systems. RESULTS: A consensus statement is presented for epilepsy mHealth CDEs. SIGNIFICANCE: Although it is not exclusive, we believe that the use of a minimal common information denominator, specifically these CDEs, will promote innovation, accelerate scientific discovery, and enhance clinical usage across applications and devices in the epilepsy mHealth space. As a consequence, people with epilepsy will have greater flexibility and ultimately more powerful tools to improve their lives.

Timing and significance of pathological features in C9orf72 expansion-associated frontotemporal dementia.

SEE SCABER AND TALBOT DOI101093/AWW264 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: A GGGGCC repeat expansion in C9orf72 leads to frontotemporal dementia and/or amyotrophic lateral sclerosis. Diverse pathological features have been identified, and their disease relevance remains much debated. Here, we describe two illuminating patients with frontotemporal dementia due to the C9orf72 repeat expansion. Case 1 was a 65-year-old female with behavioural variant frontotemporal dementia accompanied by focal degeneration in subgenual anterior cingulate cortex, amygdala, and medial pulvinar thalamus. At autopsy, widespread RNA foci and dipeptide repeat protein inclusions were observed, but TDP-43 pathology was nearly absent, even in degenerating brain regions. Case 2 was a 74-year-old female with atypical frontotemporal dementia-motor neuron disease who underwent temporal lobe resection for epilepsy 5 years prior to her first frontotemporal dementia symptoms. Archival surgical resection tissue contained RNA foci, dipeptide repeat protein inclusions, and loss of nuclear TDP-43 but no TDP-43 inclusions despite florid TDP-43 inclusions at autopsy 8 years after first symptoms. These findings suggest that C9orf72-specific phenomena may impact brain structure and function and emerge before first symptoms and TDP-43 aggregation.

Using a standalone ear-EEG device for focal-onset seizure detection.

BACKGROUND: Seizure detection is challenging outside the clinical environment due to the lack of comfortable, reliable, and practical long-term neurophysiological monitoring devices. We developed a novel, discreet, unobstructive in-ear sensing system that enables long-term electroencephalography (EEG) recording. This is the first study we are aware of that systematically compares the seizure detection utility of in-ear EEG with that of simultaneously recorded intracranial EEG. In addition, we present a similar comparison between simultaneously recorded in-ear EEG and scalp EEG. METHODS: In this foundational research, we conducted a clinical feasibility study and validated the ability of the ear-EEG system to capture focal-onset seizures against 1255 hrs of simultaneous ear-EEG data along with scalp or intracranial EEG in 20 patients with refractory focal epilepsy (11 with scalp EEG, 8 with intracranial EEG, and 1 with both). RESULTS: In a blinded, independent review of the ear-EEG signals, two epileptologists were able to detect 86.4% of the seizures that were subsequently identified using the clinical gold standard EEG modalities, with a false detection rate of 0.1 per day, well below what has been reported for ambulatory monitoring. The few seizures not detected on the ear-EEG signals emanated from deep within the mesial temporal lobe or extra-temporally and remained very focal, without significant propagation. Following multiple sessions of recording for a median continuous wear time of 13 hrs, patients reported a high degree of tolerance for the device, with only minor adverse events reported by the scalp EEG cohort. CONCLUSIONS: These preliminary results demonstrate the potential of using ear-EEG to enable routine collection of complementary, prolonged, and remote neurophysiological evidence, which may permit real-time detection of paroxysmal events such as seizures and epileptiform discharges. This study suggests that the ear-EEG device may assist clinicians in making an epilepsy diagnosis, assessing treatment efficacy, and optimizing medication titration.

Seizure diaries for clinical research and practice: limitations and future prospects.

PURPOSE: An NINDS-sponsored conference in April of 2011 reviewed issues in epilepsy clinical trials. One goal was to clarify new electronic methods for recording seizure information and other data in clinical trials. METHODS: This selective literature review and compilation of expert opinion considers advantages and limitations of traditional paper-based seizure diaries in comparison to electronic diaries. KEY FINDINGS: Seizure diaries are a type of patient-reported outcome. All seizure diaries depend first on accurate recognition and recording of seizures, which is a problem since about half of seizures recorded during video-EEG monitoring are not known to the patient. Reliability of recording is another key issue. Diaries may not be at hand after a seizure, lost or not brought to clinic visits. On-line electronic diaries have several potential advantages over paper diaries. Smartphones are increasingly accessible as data entry gateways. Data are not easily lost and are accessible from clinic. Entries can be time-stamped and provide immediate feedback, validation or reminders. Data can also can be graphed and pasted into an EMR. Disadvantages include need for digital sophistication, higher cost, increased setup time, and requiring attention to potential privacy issues. The Epilepsy Diary by epilepsy.com and Irody, Inc. has over 13,000 registrants and SeizureTracker over 10,000, and both are used for clinical and research purposes. Some studies have documented patient preference and increased compliance for electronic versus paper diaries. Seizure diaries can be challenging in the pediatric population. Children often have multiple seizure types and limited reporting of subjective symptoms. Multiple caregivers during the day require more training to produce reliable and consistent data. Diary-based observational studies have the advantages of low cost, allowing locus-of-control by the patient and testing in a "real-world" environment. Diary-based studies can also be useful as descriptive "snapshots" of a population. However, the type of information available is very different from that obtained by prospective controlled studies. The act of self-recording observations may itself influence the observation, for example, by causing the subject to attend more vigilantly to seizures after changing medication. Pivotal anti-seizure drug or device trials still mostly rely on paper-based seizure diaries. Industry is aware of the potential advantages of electronic diaries, particularly, the promise of real-time transmission of data, time-stamping of entries, reminders to subjects, and potentially automatic interfaces to other devices. However, until diaries are validated as research tools and the regulatory environment becomes clearer, adoption of new types of diaries as markers for a primary study outcome will be cautious. SIGNIFICANCE: Recommendations from the conference included: further studies of validity of epilepsy diaries and how they can be used to improve adherence; use and further development of core data sets, such as the one recently developed by NINDS; encouraging links of diaries to electronic sensors; development of diary privacy and legal policies; examination of special pediatric diary issues; development of principles for observational research from diaries; and work with the FDA to make electronic diaries more useful in industry-sponsored clinical trials.

Efficacy and safety of eslicarbazepine acetate as a first or later adjunctive therapy in patients with focal seizures.

INTRODUCTION: We report outcomes from an open-label, non-randomized, 24-week study of eslicarbazepine acetate (ESL) in adults at earlier and later stages of their treatment history for focal seizures, conducted in a real-world clinical setting. METHODS: ESL was taken as the first adjunctive therapy to levetiracetam (LEV) or lamotrigine (LTG) monotherapy (Arm 1), or as a later adjunctive therapy in treatment-resistant patients (Arm 2). The primary objective was to evaluate the effectiveness of ESL (by retention rates). Secondary objectives were to evaluate efficacy (seizure frequency), safety, tolerability, behavioral changes, mood, and health-related quality of life (HRQoL) associated with ESL treatment. RESULTS: The modified intent-to-treat population included 96 patients (Arm 1: n = 41; Arm 2: n = 55) and the safety population included 102 patients (Arm 1: n = 44; Arm 2: n = 58). Overall, 81.8 % of patients in Arm 1 and 63.8 % of patients in Arm 2 completed the 24-week maintenance period. Median reductions in standardized seizure frequency (SSF) were markedly higher in Arm 1 (72.8 %) than Arm 2 (22.8 %), as were responder rates (≥50 % reduction in SSF; Arm 1: 62.5 %; Arm 2: 38.5 %) and rates of seizure freedom (Arm 1: 25.0 %; Arm 2: 9.6 %). Efficacy outcomes were generally more favorable in patients taking ESL in combination with LEV versus other anti-seizure medications (ASMs). Treatment-emergent adverse events (TEAEs; 81 % vs 73 %) and TEAEs leading to discontinuation (16 % vs 2 %) were reported more frequently in Arm 2 than Arm 1, respectively. Serious adverse events were reported infrequently (Arm 1: 0; Arm 2: 7 %). The most common TEAEs were dizziness, nausea, headache, somnolence, fatigue, nasopharyngitis, vomiting, and anxiety. There were no notable changes in depressive symptoms, mood status, or aggression throughout the study. Health and HRQoL scores were generally high at baseline and did not change throughout the study. However, on average, both clinicians and patients perceived improvement in illness over the course of the study. CONCLUSIONS: ESL was effective and well tolerated both as the first adjunctive therapy to either of the most prescribed first-line ASMs, LEV or LTG, and as a later adjunctive therapy in treatment-resistant patients.

Stopping antiepileptic drugs: when and why?

After a patient has initiated an antiepileptic drug (AED) and achieved a sustained period of seizure freedom, the bias towards continuing therapy indefinitely can be substantial. Studies show that the rate of seizure recurrence after AED withdrawal is about two to three times the rate in patients who continue AEDs, but there are many benefits to AED withdrawal that should be evaluated on an individualized basis. AED discontinuation may be considered in patients whose seizures have been completely controlled for a prolonged period, typically 1 to 2 years for children and 2 to 5 years for adults. For children, symptomatic epilepsy, adolescent onset, and a longer time to achieve seizure control are associated with a worse prognosis. In adults, factors such as a longer duration of epilepsy, an abnormal neurologic examination, an abnormal EEG, and certain epilepsy syndromes are known to increase the risk of recurrence. Even in patients with a favorable prognosis, however, the risk of relapse can be as high as 20% to 25%. Before withdrawing AEDs, patients should be counseled about their individual risk for relapse and the potential implications of a recurrent seizure, particularly for safety and driving.

Digital tools for epilepsy: Opportunities and barriers.

This review and commentary presents and discusses the major categories of digital tools that are currently available to epilepsy patients. This review synthesizes the breadth of resources that may be used to create a comprehensive self-management platform. The manuscript organizes the discussion into the following topics: self-management education programs, electronic diaries for self-monitoring, and automated wearables for seizure detection. Despite being available for many years, these tools are utilized by only a small fraction of epilepsy patients. To directly address this, the discussion section will opine on some of the possible barriers, including a lack of historical precedent or prescribing infrastructure, a lack of financial incentives, concerns about data privacy or liability, and uncertainty about the supporting evidence for these solutions.

Neuro-Oncology Practice Clinical Debate: long-term antiepileptic drug prophylaxis in patients with glioma.

Patients with primary brain tumors often experience seizures, which can be the presenting symptom or occur for the first time at any point along the illness trajectory. In addition to causing morbidity, seizures negatively affect independence and quality of life in other ways, for example, by leading to loss of driving privileges. Long-term therapy with antiepileptic drugs (AEDs) is the standard of care in brain tumor patients with seizures, but the role of prophylactic AEDs in seizure-naive patients remains controversial. In this article, experts in the field discuss the issues of AED efficacy and toxicity, and explain their differing recommendations for routine use of prophylactic AEDs.

Assessment of the Predictive Value of Outpatient Smartphone Videos for Diagnosis of Epileptic Seizures.

Importance: Misdiagnosis of epilepsy is common. Video electroencephalogram provides a definitive diagnosis but is impractical for many patients referred for evaluation of epilepsy. Objective: To evaluate the accuracy of outpatient smartphone videos in epilepsy. Design, Setting, and Participants: This prospective, masked, diagnostic accuracy study (the OSmartViE study) took place between August 31, 2015, and August 31, 2018, at 8 academic epilepsy centers in the United States and included a convenience sample of 44 nonconsecutive outpatients who volunteered a smartphone video during evaluation and subsequently underwent video electroencephalogram monitoring. Three epileptologists uploaded videos for physicians from the 8 epilepsy centers to review. Main Outcomes and Measures: Measures of performance (accuracy, sensitivity, specificity, positive predictive value, and negative predictive value) for smartphone video-based diagnosis by experts and trainees (the index test) were compared with those for history and physical examination and video electroencephalogram monitoring (the reference standard). Results: Forty-four eligible epilepsy clinic outpatients (31 women [70.5%]; mean [range] age, 45.1 [20-82] years) submitted smartphone videos (530 total physician reviews). Final video electroencephalogram diagnoses included 11 epileptic seizures, 30 psychogenic nonepileptic attacks, and 3 physiologic nonepileptic events. Expert interpretation of a smartphone video was accurate in predicting a video electroencephalogram monitoring diagnosis of epileptic seizures 89.1% (95% CI, 84.2%-92.9%) of the time, with a specificity of 93.3% (95% CI, 88.3%-96.6%). Resident responses were less accurate for all metrics involving epileptic seizures and psychogenic nonepileptic attacks, despite greater confidence. Motor signs during events increased accuracy. One-fourth of the smartphone videos were correctly diagnosed by 100% of the reviewing physicians, composed solely of psychogenic attacks. When histories and physical examination results were combined with smartphone videos, correct diagnoses rose from 78.6% to 95.2%. The odds of receiving a correct diagnosis were 5.45 times greater using smartphone video alongside patient history and physical examination results than with history and physical examination alone (95% CI, 1.01-54.3; P = .02). Conclusions and Relevance: Outpatient smartphone video review by experts has predictive and additive value for diagnosing epileptic seizures. Smartphone videos may reliably aid psychogenic nonepileptic attacks diagnosis for some people.

The effects of epilepsy and its treatments on affect and emotion.

Epilepsy creates significant morbidity, disability, and loss of productivity worldwide. Although unpredictable seizures define epilepsy, the cognitive and emotional difficulties encountered by people with epilepsy may have an even greater impact on everyday function. Epilepsy is associated with lower quality of life (QOL); while this is partially attributable to ongoing seizures, QOL is independently affected by comorbid affective disorders like depression and anxiety. These can accompany all types of epilepsy, but may be especially noteworthy in partial epilepsy syndromes with foci in the frontal or temporal lobes. There is growing evidence that epileptogenic lesions disrupt cortical networks that carry out emotional processing. In addition to epilepsy itself, treatment strategies also affect cognitive functioning and mood. Antiepileptic drugs, vagal nerve stimulation, and surgical resection have all been associated with changes in mood, emotional processing, and social cognition. Overall, the relationship between epilepsy and emotion is vastly complex; when assessing emotional difficulties in a person with epilepsy, we must consider the psychosocial impact of the disease on the patient, the underlying pathophysiology of the disease, and the effects of ongoing treatments.

Self-Management in Epilepsy Care: Untapped Opportunities.

Constant accessibility, rapid scalability, and modest costs make digital and mobile epilepsy self-management platforms an attractive alternative to resource-intensive in-person programs.

Is seizure frequency variance a predictable quantity?

Background: There is currently no formal method for predicting the range expected in an individual's seizure counts. Having access to such a prediction would be of benefit for developing more efficient clinical trials, but also for improving clinical care in the outpatient setting. Methods: Using three independently collected patient diary datasets, we explored the predictability of seizure frequency. Three independent seizure diary databases were explored: SeizureTracker (n = 3016), Human Epilepsy Project (n = 93), and NeuroVista (n = 15). First, the relationship between mean and standard deviation in seizure frequency was assessed. Using that relationship, a prediction for the range of possible seizure frequencies was compared with a traditional prediction scheme commonly used in clinical trials. A validation dataset was obtained from a separate data export of SeizureTracker to further verify the predictions. Results: A consistent mathematical relationship was observed across datasets. The logarithm of the average seizure count was linearly related to the logarithm of the standard deviation with a high correlation (R2 > 0.83). The three datasets showed high predictive accuracy for this log-log relationship of 94%, compared with a predictive accuracy of 77% for a traditional prediction scheme. The independent validation set showed that the log-log predicted 94% of the correct ranges while the RR50 predicted 77%. Conclusion: Reliably predicting seizure frequency variability is straightforward based on knowledge of mean seizure frequency, across several datasets. With further study, this may help to increase the power of RCTs, and guide clinical practice.

Does accounting for seizure frequency variability increase clinical trial power?

OBJECTIVE: Seizure frequency variability is associated with placebo responses in randomized controlled trials (RCT). Increased variability can result in drug misclassification and, hence, decreased statistical power. We investigated a new method that directly incorporated variability into RCT analysis, ZV. METHODS: Two models were assessed: the traditional 50%-responder rate (RR50), and the variability-corrected score, ZV. Each predicted seizure frequency upper and lower limits using prior seizures. Accuracy was defined as percentage of time-intervals when the observed seizure frequencies were within the predicted limits. First, we tested the ZV method on three datasets (SeizureTracker: n=3016, Human Epilepsy Project: n=107, and NeuroVista: n=15). An additional independent SeizureTracker validation dataset was used to generate a set of 200 simulated trials each for 5 different sample sizes (total N=100 to 500 by 100), assuming 20% dropout and 30% drug efficacy. "Power" was determined as the percentage of trials successfully distinguishing placebo from drug (p<0.05). RESULTS: Prediction accuracy across datasets was, ZV: 91-100%, RR50: 42-80%. Simulated RCT ZV analysis achieved >90% power at N=100 per arm while RR50 required N=200 per arm. SIGNIFICANCE: ZV may increase the statistical power of an RCT relative to the traditional RR50.

Mobile health: the power of wearables, sensors, and apps to transform clinical trials.

Mobile technology has become a ubiquitous part of everyday life, and the practical utility of mobile devices for improving human health is only now being realized. Wireless medical sensors, or mobile biosensors, are one such technology that is allowing the accumulation of real-time biometric data that may hold valuable clues for treating even some of the most devastating human diseases. From wearable gadgets to sophisticated implantable medical devices, the information retrieved from mobile technology has the potential to revolutionize how clinical research is conducted and how disease therapies are delivered in the coming years. Encompassing the fields of science and engineering, analytics, health care, business, and government, this report explores the promise that wearable biosensors, along with integrated mobile apps, hold for improving the quality of patient care and clinical outcomes. The discussion focuses on groundbreaking device innovation, data optimization and validation, commercial platform integration, clinical implementation and regulation, and the broad societal implications of using mobile health technologies.

Interest in a digital health tool in veterans with epilepsy: results of a phone survey.

OBJECTIVE: Online tools for managing chronic health conditions are becoming increasingly popular. Perceived benefits include ease of use, low costs, and availability but are contingent on patient engagement, Internet access, and digital literacy. This article describes data collected during the recruitment phase of a study evaluating an online self-management platform for epilepsy in a U.S. Veteran population. METHODS: We used administrative data to identify and contact Veterans with a likely diagnosis of epilepsy in the Veterans Health Administration (VHA). Veterans who did not respond directly to a mailed invitation were recruited by phone to determine study interest and evaluate digital access. RESULTS: Of the 2,143 Veterans mailed study invitations, phone calls were made to 1,789 who did not specifically decline participation. Among those reached by phone (n = 1,053): 295 (28%) expressed interest in the study and an online tool, 333 (19%) reported a lack of computer and/or Internet access and 425 (40%) were not interested for other reasons. CONCLUSIONS: This study suggests an interest in online tools for managing health despite the fact that some Veterans lack computer and/or Internet access. As investment in digital health solutions grows, the VHA should prioritize the widespread provision of digital access to more Veterans.

Patients optimizing epilepsy management via an online community: the POEM Study.

OBJECTIVE: The study objective was to test whether engaging in an online patient community improves self-management and self-efficacy in veterans with epilepsy. METHODS: The study primary outcomes were validated questionnaires for self-management (Epilepsy Self-Management Scale [ESMS]) and self-efficacy (Epilepsy Self-Efficacy Scale [ESES]). Results were based on within-subject comparisons of pre- and postintervention survey responses of veterans with epilepsy engaging with the PatientsLikeMe platform for a period of at least 6 weeks. Analyses were based on both completer and intention-to-treat scenarios. RESULTS: Of 249 eligible participants enrolled, 92 individuals completed both surveys. Over 6 weeks, completers improved their epilepsy self-management (ESMS total score from 139.7 to 142.7, p = 0.02) and epilepsy self-efficacy (ESES total score from 244.2 to 254.4, p = 0.02) scores, with greatest impact on an information management subscale (ESMS-information management total score from 20.3 to 22.4, p < 0.001). Results were similar in intention-to-treat analyses. Median number of logins, postings to forums, leaving profile comments, and sending private messages were more common in completers than noncompleters. CONCLUSIONS: An internet-based psychosocial intervention was feasible to implement in the US veteran population and increased epilepsy self-management and self-efficacy scores. The greatest improvement was noted for information management behaviors. Patients with chronic conditions are increasingly encouraged to self-manage their condition, and digital communities have potential advantages, such as convenience, scalability to large populations, and building a community support network. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that for patients with epilepsy, engaging in an online patient community improves self-management and self-efficacy.